Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two widely used neuroimaging techniques, with complementary strengths and weaknesses. Predicting fMRI activity from ...
Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...
This project predicts loan approval outcomes (Approved/Rejected) using a PyTorch neural network. It includes data preprocessing, train/validation/test split, model training with BCEWithLogitsLoss, and ...
Introduction: Most farmers in Nigeria lack knowledge of their farmland’s nutrient content, often relying on intuition for crop cultivation. Even when aware, they struggle to interpret soil information ...
This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch. Dropout in Neural Network is a regularization technique in Deep Learning to ...
ABSTRACT: Bipolar disorder is a multifaceted psychiatric illness characterized by unpredictable mood episodes and highly variable treatment responses across individuals. Predicting response to ...
This project implements a robust time series forecasting pipeline to predict the closing prices of the IBOVESPA index, Brazil’s main stock market benchmark. It combines advanced data preprocessing ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Receptor tyrosine kinases (RTKs) are key regulators of cellular signaling and are ...
Abstract: Electronic design automation (EDA) has unique challenges for addressing the design of systems for emerging applications due to the complexities involved, where multiple chiplets are ...
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